AI and Ethics

Image taken from public domain

Image courtesy of Mike MacKenzie

AI and Ethics

January 2022

Artificial intelligence (AI) applications have made their way into business, including customer and sales analysis, fraud detection, hiring and recruitment, and cybersecurity,

Customer intelligence has grown out of customer and sales analysis using AI techniques.

AI applications in cybersecurity can use image recognition software allows for rapid identification of common images or people using programmed pattern recognition through deep learning techniques or neural networks. But ethical issues such as improper identification, can be a liability.

Issues of privacy, fairness and accountability of AI in hiring and recruitment in employment and human raise concerns of bias in the selection process, data collection of candidates and their information.

The common themes of the practical implications and outcomes of AI applications in these arenas arise out of data collection, its assessment or analysis and any underlying bias applied to the process. Ethical guidelines for AI applications center around transparency, justice and fairness, safety (non-maleficence), responsibility, and privacy. These are the principles that have created the movement and focus of “Responsible AI.” AI ethicists and influencers such as Dylan Thomas Doyle and David Polger help to illuminate these issues for accessibility.

In my next post I’ll discuss these challenges in the field of health care and highlight some of the recent advances in some AI applications.